OMIP-002: Phenotypic analysis of specific human CD8+ T-cells using peptide-MHC class I multimers for any of four epitopes

Analysis of Antigen-Specific T and B Cells for Monitoring Immune Protection Against SARS-CoV-2

Immunological memory is the basis of protection against most pathogens. Long-living memory T and B cells able to respond to specific stimuli, as well as persistent antibodies in plasma and in other body fluids, are crucial for determining the efficacy of vaccination and for protecting from a second infection by a previously encountered pathogen. Antigen-specific cells are represented at a very low frequency in the blood, and indeed, they can be considered "rare events" present in the memory T-cell pool. Therefore, such events should be analyzed with careful attention. In the last 20 years, different methods, mostly based upon flow cytometry, have been developed to identify such rare antigen-specific cells, and the COVID-19 pandemic has given a dramatic impetus to characterize the immune response against the virus. In this regard, we know that the identification, enumeration, and characterization of SARS-CoV-2-specific T and B cells following infection and/or vaccination require i) the use of specific peptides and adequate co-stimuli, ii) the use of appropriate inhibitors to avoid nonspecific activation, iii) the setting of appropriate timing for stimulation, and iv) the choice of adequate markers and reagents to identify antigen-specific cells. Optimization of these procedures allows not only determination of the magnitude of SARS-CoV-2-specific responses but also a comparison of the effects of different combinations of vaccines or determination of the response provided by so-called "hybrid immunity," resulting from a combination of natural immunity and vaccine-generated immunity. Here, we present two methods that are largely used to monitor the response magnitude and phenotype of SARS-CoV-2-specific T and B cells by polychromatic flow cytometry, along with some tips that can be useful for the quantification of these rare events. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Identification of antigen-specific T cells Basic Protocol 2: Identification of antigen-specific B cells.

A mine is a terrible thing to waste: high content, single cell technologies for comprehensive immune analysis

In recent years, an incredible variety of single cell technologies have become available to analyze immune responses. These technologies include polychromatic flow cytometry, mass cytometry, highly multiplexed single cell qPCR, RNA sequencing, microtools, and high-resolution imaging. In this article, we review these platforms, describing their power and limitations for comprehensive analysis of the immune system. We relate the properties of these technologies to the various cellular states relevant to an immune response, in order to address which technologies are most appropriate for which settings.

RchyOptimyx: cellular hierarchy optimization for flow cytometry

Analysis of high-dimensional flow cytometry datasets can reveal novel cell populations with poorly understood biology. Following discovery, characterization of these populations in terms of the critical markers involved is an important step, as this can help to both better understand the biology of these populations and aid in designing simpler marker panels to identify them on simpler instruments and with fewer reagents (i.e., in resource poor or highly regulated clinical settings). However, current tools to design panels based on the biological characteristics of the target cell populations work exclusively based on technical parameters (e.g., instrument configurations, spectral overlap, and reagent availability). To address this shortcoming, we developed RchyOptimyx (cellular hieraRCHY OPTIMization), a computational tool that constructs cellular hierarchies by combining automated gating with dynamic programming and graph theory to provide the best gating strategies to identify a target population to a desired level of purity or correlation with a clinical outcome, using the simplest possible marker panels. RchyOptimyx can assess and graphically present the trade-offs between marker choice and population specificity in high-dimensional flow or mass cytometry datasets. We present three proof-of-concept use cases for RchyOptimyx that involve 1) designing a panel of surface markers for identification of rare populations that are primarily characterized using their intracellular signature; 2) simplifying the gating strategy for identification of a target cell population; 3) identification of a non-redundant marker set to identify a target cell population.

Holoendemic malaria exposure is associated with altered Epstein-Barr virus-specific CD8(+) T-cell differentiation

Coinfection with Plasmodium falciparum malaria and Epstein-Barr virus (EBV) is a major risk factor for endemic Burkitt lymphoma (eBL), still one of the most prevalent pediatric cancers in equatorial Africa. Although malaria infection has been associated with immunosuppression, the precise mechanisms that contribute to EBV-associated lymphomagenesis remain unclear. In this study, we used polychromatic flow cytometry to characterize CD8(+) T-cell subsets specific for EBV-derived lytic (BMFL1 and BRLF1) and latent (LMP1, LMP2, and EBNA3C) antigens in individuals with divergent malaria exposure. No malaria-associated differences in EBV-specific CD8(+) T-cell frequencies were observed. However, based on a multidimensional analysis of CD45RO, CD27, CCR7, CD127, CD57, and PD-1 expression, we found that individuals living in regions with intense and perennial (holoendemic) malaria transmission harbored more differentiated EBV-specific CD8(+) T-cell populations that contained fewer central memory cells than individuals living in regions with little or no (hypoendemic) malaria. This profile shift was most marked for EBV-specific CD8(+) T-cell populations that targeted latent antigens. Importantly, malaria exposure did not skew the phenotypic properties of either cytomegalovirus (CMV)-specific CD8(+) T cells or the global CD8(+) memory T-cell pool. These observations define a malaria-associated aberration localized to the EBV-specific CD8(+) T-cell compartment that illuminates the etiology of eBL.